Computers and networks have ushered in what has been called the “information age”. There is a massive quantity of data available that can assist users in doing a variety of tasks, including making predictions regarding a future value of a parameter. For instance, by performing regression analysis on time series data of a parameter, predictions can be made about future time series of the data. Such predictions may be performed for any of a variety of reasons including, for instance, anticipating power usage within a data center, predicting network traffic over a certain channel, predicting processor usage, estimating future world surface temperatures, and so forth. By accurately predicting future values of such parameters, appropriate preparations can be made to respond to anticipated future change.
However, it represents an extremely difficult technical challenge to predict how the future can affect something, especially when relying only upon the time series data from the past alone. Accordingly, there are conventional mechanism that improve predictive technique by factoring in knowledge of periodic fluctuations. There are also conventional mechanisms that factor in external factors that are distinct from the time series data and the parameter, but nevertheless may have some influence upon that parameter.
The subject matter claimed herein is not limited to embodiments that solve any disadvantages or that operate only in environments such as those described above. Rather, this background is only provided to illustrate one exemplary technology area where some embodiments described herein may be practiced.